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ESEM
2008
ACM
13 years 9 months ago
Fit data selection for software effort estimation models
To construct a better multivariate regression model for software effort estimation, this paper proposes a method to select projects as a fit data from a given project data set bas...
Koji Toda, Akito Monden, Ken-ichi Matsumoto
CSDA
2006
145views more  CSDA 2006»
13 years 7 months ago
Improved predictions penalizing both slope and curvature in additive models
A new method is proposed to estimate the nonlinear functions in an additive regression model. Usually, these functions are estimated by penalized least squares, penalizing the cur...
Magne Aldrin
ICDM
2005
IEEE
134views Data Mining» more  ICDM 2005»
14 years 1 months ago
A Preference Model for Structured Supervised Learning Tasks
The preference model introduced in this paper gives a natural framework and a principled solution for a broad class of supervised learning problems with structured predictions, su...
Fabio Aiolli
TSP
2008
166views more  TSP 2008»
13 years 7 months ago
Linear Regression With Gaussian Model Uncertainty: Algorithms and Bounds
In this paper, we consider the problem of estimating an unknown deterministic parameter vector in a linear regression model with random Gaussian uncertainty in the mixing matrix. W...
Ami Wiesel, Yonina C. Eldar, Arie Yeredor
CONCUR
2003
Springer
14 years 25 days ago
Multi-Valued Model Checking via Classical Model Checking
Multi-valued model-checking is an extension of classical model-checking to reasoning about systems with uncertain information, which are common during early design stages. The addi...
Arie Gurfinkel, Marsha Chechik